Petabyte scale- Redshift

Data ingestion through Kinesis data streams will require manual intervention to provide more shards as data size grows. Kinesis firehose will ingest data with the least operational overhead.

Kinesis data stream cannot detined to s3

1- Kinesis Data Stream provides a fully managed platform for custom data processing and analysis. Or we can say that used for custom data processing and analysis which required more manual intervention. 2- Kinesis Data Firehose simplifies the delivery of streaming data to various destinations without the need for complex transformations. Option B is more suitable for the given scenario.

always if you have a service that is meant for a specific job, it the correct answer, is logic. "A" is not good enough for this situation

B. Send activity data to an Amazon Kinesis Data Firehose delivery stream. Configure the stream to deliver the data to an Amazon Redshift cluster.

Petabyte scale- Redshift

1- Kinesis Data Stream provides a fully managed platform for custom data processing and analysis. Or we can say that used for custom data processing and analysis which required more manual intervention. 2- Kinesis Data Firehose simplifies the delivery of streaming data to various destinations without the need for complex transformations. Option B is more suitable for the given scenario.

Petabyte Scale sounds like Redshift!

B provides a fully managed and scalable solution for data ingestion and analytics. KDF simplifies the data ingestion process by automatically scaling to handle large volumes of streaming data. It can directly load the data into an Redshift cluster, which is a powerful and fully managed data warehousing solution. A. While Kinesis can handle streaming data, it requires additional processing to load the data into an analytics solution. C. Although S3 and Lambda can handle the storage and processing of data, it requires more manual configuration and management compared to the fully managed solution offered by KDF and Redshift. D. This option involves more operational overhead, as it requires managing and scaling the EC2 instances and RDS database infrastructure manually. Therefore, option B with KDF delivering the data to Redshift cluster offers the most streamlined and operationally efficient solution for ingesting and analyzing the user activity data in the given scenario.

petabytes in size => redshift

It's A. Data Stream is better in this case, and you can query data in S3 with Athena

Option B is correct answer.

This solution meets the requirements as follows: • Kinesis Data Firehose can scale to ingest and process multiple terabytes per hour of streaming data. This can easily handle the petabyte-scale data volumes. • Firehose can deliver the data to Redshift, a petabyte-scale data warehouse, enabling on-demand SQL analytics of the data. • Redshift is a fully managed service, minimizing operational overhead. Firehose is also fully managed, handling scalability, availability, and durability of the streaming data ingestion.

B: The answer is certainly option "B" because ingesting user activity data can easily be handled by Amazon Kinesis Data streams. The ingested data can then be sent into Redshift for Analytics. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift Serverless lets you access and analyze data without all of the configurations of a provisioned data warehouse. https://docs.aws.amazon.com/redshift/latest/mgmt/welcome.html

the Key sentence here is: "that facilitates on-demand analytics", tthats the reason because we need to choose Kinesis Data streams over Data Firehose

B: Kinesis Data Firehose service automatically load the data into Amazon Redshift and is a petabyte-scale data warehouse service. It allows you to perform on-demand analytics with minimal operational overhead. Since the requirement didn't state what kind of analytics you need to run, we can assume that we do not need to set up additional services to provide further analytics. Thus, it has the least operational overhead. Why not A: It is a viable solution, but storing the data in S3 would require you to set up additional services like Amazon Redshift or Amazon Athena to perform the analytics.